ar_coef

Computes estimator of the AR(p) coefficients by the procedure from
Khismatullina and Vogt (2020).

internal

Performs a multiscale analysis of a nonparametric
regression or nonparametric regressions with time series errors. In case
of one regression, with the help of this package it is possible to detect
the regions where the trend function is increasing or decreasing.
In case of multiple regressions, the test identifies regions where
the trend functions are different from each other. See
Khismatullina and Vogt (2020) <doi:10.1111/rssb.12347>,
Khismatullina and Vogt (2022) <doi:10.48550/arXiv.2209.10841> and
Khismatullina and Vogt (2023) <doi:10.1016/j.jeconom.2021.04.010>
for more details on theory and applications.

Marina Khismatullina

MSinference

Multiscale Inference for Nonparametric Time Trend(s)

Michael Vogt

ar_coef function

<dl><dt>data</dt>
<dd>Time series.</dd>
<dt>l1, l2</dt>
<dd>Tuning parameters.</dd>
<dt>correct</dt>
<dd>Vector of the corrections, either zero or calculated by
the function <code>corrections</code>.</dd>
<dt>p</dt>
<dd>AR order of the time series.</dd></dl>

Arguments

Computes estimator of the AR(p) coefficients by the procedure from
Khismatullina and Vogt (2020). — ar_coef

<dl>

<dt>data</dt>
<dd>Time series.</dd>


<dt>l1, l2</dt>
<dd>Tuning parameters.</dd>


<dt>correct</dt>
<dd>Vector of the corrections, either zero or calculated by
the function <code>corrections</code>.</dd>


<dt>p</dt>
<dd>AR order of the time series.</dd>

</dl>

ar_coef: Computes estimator of the AR(p) coefficients by the procedure from Khismatullina and Vogt (2020).

Description

Usage

Value

Arguments